极端空间环境目标精细感知综述

With the advancement of space technology, precise perception of space objects plays a vital role in dynamic monitoring, deformation analysis, and orbital rendezvous. However, challenges such as image degradation in extreme space environments, highly dynamic scenes, and multimodal fusion issues limit the accuracy and efficiency of perception. This paper focuses on three core issues in the precise perception of fine-grained objects in extreme space environments: low-quality image enhancement, 3D reconstruction of objects, and object pose estimation, analyzing their research progress and challenges. For low-quality image enhancement, we review classical methods in denoising, deblurring, and super-resolution, discussing the approaches and advantages and disadvantages of various methods in addressing extreme lighting conditions, various types of noise, and other interferences. For 3D object reconstruction, we explore optimization strategies in dynamic scenes by integrating optical reconstruction with point cloud registration technologies. For object pose estimation, we analyze sensor reliability and high-precision inference methods in highly dynamic environments. The paper presents a chronological timeline of method development, a classification diagram of methodologies, and tables summarizing databases and evaluation metrics, providing a comprehensive overview and reference for research on extreme space perception. Furthermore, it discusses critical bottlenecks that need to be addressed in the future to advance new technologies for precise perception in extreme space environments.